Soil Moisture Retrieval With Remote Sensing
Images For Debris Flow Forecast In
Humid Regions
Author(s)
Y. Zhao, H. Yang & F. Wei
Abstract
Soil moisture is a key parameter in debris flow prediction for its influence on the
critical rainfall triggering debris flow. Soil moisture can be obtained by ground
measurement. However, it is difficult to extend these limited observing data to
the regional scale because of the heterogeneity of land surface. The Temperature-
Vegetation Dryness Index (TVDI) is a common method of estimating regional
soil moisture by the images of MODIS, because of its moderate spatial resolution
and high temporal resolution. However, because the basic assumption of the
TVDI method is that pixels from the study region can cover the entire range of
soil moisture conditions and vegetation fractions, it is difficult to determine the
actual dry edge of the space in humid regions. The Crop Water Shortage Index
(CWSI) calculated by actual evapotranspiration and potential evapotranspiration
does not need fitting to the dry edge and wet edge. CWSI further considers about
the influence of vegetation. In this paper, we applied both TVDI and CWSI
methods to retrieving soil moisture using remote sensing and meteorological data
in Zhejiang Province, which has a humid climate. Among CWSI, the actual and
potential evapotranspiration are calculated by the SEBS model. CWSI can also
directly express the extent of soil moisture. In surface soil (0-10cm), the
correlation coefficient of CWSI and measured relative soil moisture (RSM)
reached -0.89.
Keywords: remote sensing, soil moisture, TVDI, CWSI, debris flow forecast,
humid region.
Keywords
remote sensing, soil moisture, TVDI, CWSI, debris flow forecast,
humid region
Related Book
Other papers in this volume
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